sklearn.datasets.load_boston¶

sklearn.datasets.load_boston(return_X_y=False)[source]¶

Load and return the boston house-prices dataset (regression).

Samples total	506
Dimensionality	13
Features	real, positive
Targets	real 5. - 50.

Read more in the User Guide.

Parameters

return_X_yboolean, default=False.

If True, returns (data, target) instead of a Bunch object. See below for more information about the data and target object.

New in version 0.18.

Returns

dataBunch

Dictionary-like object, the interesting attributes are: ‘data’, the data to learn, ‘target’, the regression targets, ‘DESCR’, the full description of the dataset, and ‘filename’, the physical location of boston csv dataset (added in version 0.20).

(data, target)tuple if return_X_y is True

New in version 0.18.

Notes

Changed in version 0.20: Fixed a wrong data point at [445, 0].

Examples

>>> from sklearn.datasets import load_boston
>>> X, y = load_boston(return_X_y=True)
>>> print(X.shape)
(506, 13)

Examples using sklearn.datasets.load_boston¶

Advanced Plotting With Partial Dependence¶

Plot individual and voting regression predictions¶

Gradient Boosting regression¶

Combine predictors using stacking¶

Outlier detection on a real data set¶

Model Complexity Influence¶

Feature selection using SelectFromModel and LassoCV¶

Imputing missing values before building an estimator¶

Plotting Cross-Validated Predictions¶

Effect of transforming the targets in regression model¶